Smartphones, laptops, and data centers are CMOS-based technologies that ushered our world into the information age of the 21st century. Despite their advantages for scalable computing, their implementations come with surprisingly large energetic costs. This challenge has revitalized scientific and engineering interest in energy-efficient information-processing designs. One current paradigm -- dynamical computing -- controls the location and shape of minima in potential energy landscapes that are connected to a thermal environment. The landscape supports distinguishable metastable energy minima that serve as a system's mesoscopic memory states. Information is represented by microstate distributions. Dynamically manipulating the memory states then corresponds to information processing. This framing provides a natural description of the associated thermodynamic transformations and required resources. Appealing to bifurcation theory, a computational protocol in the metastable regime can be analyzed by tracking the evolution of fixed points in the state space. We illustrate the paradigm's capabilities by performing 1-bit and 2-bit computations with double-well and quadruple-well potentials, respectively. These illustrate how dynamical computing can serve as a basis for designing universal logic gates and investigating their out-of-equilibrium thermodynamic performance.

翻译：智能手机、笔记本电脑和数据中心等基于CMOS的技术引领世界进入了21世纪的信息时代。尽管它们在可扩展计算方面具有优势，但其实现却伴随着惊人的巨大能量成本。这一挑战重新激发了科学界和工程界对高能效信息处理设计的兴趣。当前的一种范式——动力学计算——通过控制与热环境相耦合的势能景观中极小值的位置和形状来实现计算。该能量景观支持可区分的亚稳态能量极小值，这些极小值构成了系统的介观记忆状态。信息通过微观状态分布来表示。动态操控这些记忆状态即对应于信息处理过程。这一框架为相关的热力学变换及所需资源提供了自然的描述。借助分岔理论，可通过追踪状态空间中不动点的演化来分析亚稳态区域的计算协议。我们分别通过双势阱和四势阱势能实现1比特和2比特计算，以此展示该范式的计算能力。这些示例说明了动力学计算如何作为设计通用逻辑门并研究其非平衡热力学性能的基础。